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307,134 tools. Last updated 2026-07-17 01:52

"namespace:io.github.Rarefied-Earth" matching MCP tools:

  • Returns all 14 cards in a given Minor Arcana suit as a structured array. SECTION: WHAT THIS TOOL COVERS Each of the four suits has 14 cards: Ace through 10 plus Page, Knight, Queen, King. Elemental associations: Wands=fire (action, career, creativity), Cups=water (emotions, relationships, intuition), Swords=air (intellect, conflict, truth), Pentacles=earth (material, money, body, practical matters). SECTION: WORKFLOW BEFORE: None — standalone. AFTER: None. SECTION: INPUT CONTRACT suit — One of exactly: 'wands', 'cups', 'swords', 'pentacles'. Case-insensitive. Any other value is rejected locally with MCP INVALID_PARAMS. SECTION: OUTPUT CONTRACT data[] — 14 card objects for the requested suit, each identical to asterwise_get_tarot_card output. Ordered Ace through King. SECTION: RESPONSE FORMAT response_format=json — array of 14 card objects. response_format=markdown — formatted list. SECTION: COMPUTE CLASS FAST_LOOKUP SECTION: ERROR CONTRACT INVALID_PARAMS (local): — suit not in {wands, cups, swords, pentacles} → MCP INVALID_PARAMS immediately. INTERNAL_ERROR: Any upstream API failure → MCP INTERNAL_ERROR SECTION: DO NOT CONFUSE WITH asterwise_get_tarot_major_arcana — 22 Major Arcana, not suit-based. asterwise_get_tarot_cards — full 78-card catalogue.
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  • Find air-quality monitoring stations (measured by physical sensors, not modeled) near a point, within a bounding box, or by country. Returns each station's id, name, coordinates, distance from the query point (when searching by coordinates), country, provider, the parameters its sensors measure, and the timestamp of its most recent data (datetimeLast). Required first step: openaq_get_readings and openaq_get_measurements key on the location id this returns. Coverage is uneven and real — a station only reports the parameters it measures, and the absence of a nearby station means no monitoring there, not clean air. For dense modeled coverage anywhere on Earth, use open-meteo-mcp-server's air-quality tool instead.
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  • Returns all 12 tropical zodiac signs (Aries, Taurus, Gemini, Cancer, Leo, Virgo, Libra, Scorpio, Sagittarius, Capricorn, Aquarius, Pisces) with essential information: name, symbol, element (fire, earth, air, water), date ranges, and short descriptions. Perfect for zodiac sign lists, horoscope widgets, birth chart calculators, astrology apps, star sign selectors, and zodiac reference tools. Use GET /signs/{id} for complete zodiac sign profiles with personality traits, compatibility, and detailed characteristics.
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  • Read the signed facts at a canonical address (cell64); auto-materializes on a miss for any band with a registered materializer. A fact_cid names one signed attestation, so a recalled fact is citeable and re-verifiable rather than a paraphrase: resolving it anywhere returns those exact bytes. It is NOT a fingerprint of the observation. The digest covers the responder's key and the moment it signed, so two responders that measure the same thing mint different fact_cids and a cid resolves only at the responder that signed it; use emem_entity for identity that crosses responders. Pass `deterministic:true` (or a `provenance` class list) to keep only facts recomputable from the cited raw source, with no model or human in the loop. In the memory algebra this is ensure(cell, bands), not get: state what must exist and the responder reuses or materializes. When to use: Call after `emem_locate` (or with a known cell64). Returns every Primary fact stored at that (cell, band, tslot). IMPORTANT: if the cell has no fact yet for a requested band AND that band has `has_materializer=true` (per `emem_coverage_matrix` / `emem_materializers`), the responder fetches the upstream value, signs it under its identity, persists it, and returns it in the same response (slower on the first call while the upstream is fetched; fast once cached). So for any wired band you can recall ANY cell on Earth without seeding, just pass `bands: [<band>]`. The response carries `materialize_notes` listing what was just fetched. Empty result with no notes means the band has no materializer at this responder.
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  • Calculate a complete Western natal chart using the tropical zodiac and Swiss Ephemeris. Returns 10 planet positions with Placidus (or chosen) house placements, essential dignities, all active aspects, and element/modality/hemisphere balance statistics. SECTION: WHAT THIS TOOL COVERS Tropical natal chart: Sun, Moon, Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, Pluto. Each planet returns tropical longitude, sign, house (1–12), retrograde flag, dignity label (domicile/exaltation/detriment/fall/peregrine), dignity score (domicile +5, exaltation +4, triplicity +3, term +2, face +1, detriment -5, fall -4), is_exaltation_degree (within 1° of exact exaltation), dignity_disputed (true for outer planets where exaltation/fall is disputed among modern astrologers). Aspect orbs: conjunction/opposition 5°, square/trine 5°, sextile 3°, minor aspects 1.5°. Not Vedic sidereal (asterwise_get_natal_chart). SECTION: WORKFLOW BEFORE: None — this tool is standalone. AFTER: asterwise_get_western_transits_daily — layer current transits over this natal chart. AFTER: asterwise_get_western_synastry — compare this chart against a partner's chart. AFTER: asterwise_get_western_solar_return — annual return chart for the current year. SECTION: INPUT CONTRACT birth.date — YYYY-MM-DD. Example: '1985-11-12' birth.time — HH:MM (24-hour local time). Example: '06:45' birth.lat — Decimal degrees, north positive. Example: 19.076 (Mumbai) birth.lon — Decimal degrees, east positive. Example: 72.8777 (Mumbai) birth.timezone — IANA timezone string. Example: 'Asia/Kolkata', 'America/New_York', 'Europe/Rome', 'UTC'. Default: UTC. IMPORTANT: Timezone defaults to UTC — always supply the correct local timezone for accurate house cusps. An incorrect timezone shifts the Ascendant. birth.house_system — 'placidus' (default, most common), 'koch', 'equal', 'whole_sign'. Placidus is standard for most Western traditions. Whole sign is traditional/Hellenistic. NOTE: house_system is accepted here but silently ignored by transit, return, synastry, composite, and progression endpoints — those always use the birth location coordinates without house-system selection. ayanamsa — always tropical regardless of any value supplied; field is not present. SECTION: OUTPUT CONTRACT data.zodiac (string — 'tropical') data.house_system (string — the system used) data.ascendant — { longitude (float), sign (string), sign_index (int 0–11), degree_in_sign (float) } data.mc — same shape as ascendant data.planets[] — 10 objects (Sun through Pluto): name (string), longitude (float), sign (string), sign_index (int 0–11) degree_in_sign (float), house (int 1–12) is_retrograde (bool), dignity (string), dignity_score (int) is_exaltation_degree (bool), dignity_disputed (bool) data.houses[] — 12 objects: house (int 1–12), cusp_longitude (float), sign (string) sign_index (int 0–11), degree_in_sign (float) data.aspects[] — each: planet_a (string), planet_b (string), type (string) exact_angle (float), orb (float), is_applying (bool) data.elements — { fire (int), earth (int), air (int), water (int), dominant (string) } data.modalities — { cardinal (int), fixed (int), mutable (int), dominant (string) } data.hemisphere — { eastern (int), western (int), northern (int), southern (int) } data.ayanamsa_value (float — 0.0 for tropical) data.ayanamsa_used (string — 'tropical') data.birth_time_provided (bool) SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON — use this for programmatic parsing, typed clients, and downstream tool chaining. response_format=markdown renders the same data as a human-readable natal report. Both modes return identical underlying data. SECTION: COMPUTE CLASS MEDIUM_COMPUTE (~300ms) SECTION: ERROR CONTRACT INVALID_PARAMS (local — caught before upstream call): — WesternBirthData Pydantic violations (date pattern, time pattern, lat/lon bounds) → MCP INVALID_PARAMS INVALID_PARAMS (upstream): — None expected for valid coordinates and dates post-1800. INTERNAL_ERROR: — Any upstream API failure or timeout → MCP INTERNAL_ERROR Edge cases: — Polar latitudes (above ~65°N or below ~65°S) may cause Placidus house calculation failure; use whole_sign or equal house system for polar births. — time='00:00' accepted; lagna-sensitive results are unreliable for unknown birth times. SECTION: DO NOT CONFUSE WITH asterwise_get_natal_chart — Vedic sidereal chart using Lahiri ayanamsa; different zodiac, different house system, different planet set (9 grahas vs 10 tropical planets). asterwise_get_western_aspects — takes raw longitudes as input; use when you already have positions and don't need full chart computation.
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  • Sign-to-sign compatibility without birth data. Based on element and modality affinity. Fast — no ephemeris calculation required. SECTION: WHAT THIS TOOL COVERS Lookup table compatibility using sign elements (fire/earth/air/water) and modalities (cardinal/fixed/mutable). No houses, no Moon phase, no Venus Mars geometry. SECTION: WORKFLOW BEFORE: None — no birth data needed. AFTER: asterwise_get_western_compatibility — when full charts are available. SECTION: INPUT CONTRACT sign1, sign2 — English zodiac names (Aries … Pisces). SECTION: OUTPUT CONTRACT data.sign1, data.sign2 data.element1, data.element2 data.modality1, data.modality2 data.element_affinity, data.modality_affinity — 'harmonious'|'neutral'|'challenging' data.overall_score (int 0-100) data.description (string) SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON. response_format=markdown renders the same data as a human-readable report. Both modes return identical underlying data. SECTION: COMPUTE CLASS FAST_LOOKUP — no ephemeris, pure table lookup. SECTION: ERROR CONTRACT INVALID_PARAMS (local): None — sign validation upstream. INTERNAL_ERROR: Any upstream API failure → MCP INTERNAL_ERROR SECTION: DO NOT CONFUSE WITH asterwise_get_western_compatibility — requires full birth data, more accurate. asterwise_get_western_synastry — aspect geometry between two full charts.
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  • MCP server for Mireye Earth — federal-source-cited geospatial data for any MCP-aware agent.

  • MCP company-state feed for SMBs. Prove live in <10s anonymously; tenant feed after trial.

  • Query the verified FCC satellite licensing docket — every space-station (SAT) filing in the FCC's own daily IBFS database dump, back to the 1960s — by applicant, application type, status, and filing date. Use this for "who is authorized to operate what in orbit, what has been filed, and where does each filing stand" questions — the satellite-buildout licensing pipeline. Each filing carries the FCC's public filing key (`file_number`, e.g. "SATLOA2025061800149"), the `callsign` (e.g. "S3069" = SpaceX Gen2), the application type and status in the FCC's OWN vocabulary — verbatim codes plus the FCC's own decode text from the same dump vintage (`app_type_code` "LOA" = Launch and Operating Authority, "STA" = Special Temporary Authority, "MOD" = Modification; `status_code` "A/C" = Action Complete, "ATPN" = Action Taken Public Notice — codebooks in describe) — the full lifecycle date family (filed / granted / expires / …), the FCC's plain-English `description` of the filing, and the applicant identity (`applicant_name`, the FCC's verbatim registrant, e.g. "Space Exploration Holdings, LLC"). Filter by `applicant_name`, `app_type_code`, `status_code`, `callsign`, `file_number`, `state` (the APPLICANT's address state), `applicant_country`, `report_period` (the filing date) via `report_period_from`/`report_period_to`, or `date_grant`/`date_expire` ranges. Group by any of `applicant_name`, `app_type_code`, `status_code`, `state`, `applicant_country`. Pass each parameter as a top-level key of `params` (flat — not nested under a `filter`, `filters`, or `where` key). Example: `{"applicant_name": "Space Exploration Holdings, LLC", "group_by": ["app_type_code"]}` for one operator's filing mix; `{"report_period_from": "2020-01-01", "group_by": ["applicant_name"], "order_by": "source_record_count", "top_n": 10}` for the most active filers of the 2020s. Returns JSON aggregates with citations and optional row-level records when `include_records` is true — every record cites its exact row in the FCC's dump, re-verifiable via get_source_evidence_v1. THE ENGRAVED BOUNDARY: new-filing intake into IBFS structurally ENDED at the FCC's ICFS system cutover (~mid-2025), and ICFS publishes no bulk data — so filings SUBMITTED after the cutover are not in this docket, and counts near/after 2025 UNDERCOUNT new filing activity (say so when answering; every response carries an icfs_cutover note). Status and lifecycle updates on the filings that ARE here continue to flow daily. A filing is an authorization EVENT: never a satellite count (one NGSO grant can cover thousands of satellites), never an orbital catalog (satellites in orbit are not served here), never launch activity (FAA data, not served here). `state`/`applicant_city` are the APPLICANT's mailing address — satellites are not in states. Earth stations (SES) and non-satellite FCC dockets are out of scope. The one measure is `source_record_count` (filings in scope).
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  • The map of emem's tool surface, and the only tool you need to find the rest. Returns the working loop in the order you walk it (name a thing, ground it, cite it, resolve it, verify it, check for drift), then every other tool grouped by the question it answers, each with its one-line trigger. Pass `name` to get one tool's full input schema and a runnable example, so you can use a tool without loading all of the descriptors into context. This endpoint advertises the core loop only; the Earth-observation, search, embedding and log tools are catalogued here and remain callable by name. When to use: Call this FIRST when you do not know which emem tool answers the question, or when you need a capability you cannot see in your tool list. This responder advertises a small core loop by default rather than its full catalog, so a tool being absent from your list does not mean it is absent from the server. Pass `q` to search by topic (`ndvi`, `cloud`, `flood`, `verify`), `name` for one tool's exact schema, or no arguments for the whole map. If you want the full catalog registered as callable tools instead, reconnect to the /mcp/full endpoint; for a one-shot answer without picking a primitive at all, use emem_ask.
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  • Verify a signed receipt envelope server-side: recomputes the canonical preimage (preimage v1: tagged, length-prefixed segments; receipts without `preimage_version` verify under the legacy `request_id | served_at | primitive | cells, | fact_cids,` concatenation), runs ed25519 over the embedded pubkey + signature, and returns `{valid, reason, pubkey_b32}`. Use when the in-browser /verify path is blocked (CDN offline, agent runtime has no crypto) or when you want a server-side audit of a third-party receipt. Algebra: verify. When to use: Pass a receipt object exactly as returned by any read primitive (signature can be byte[] or sig_b32; pubkey can be byte[] or responder_pubkey_b32 — the verifier tolerates both shapes). Optionally override `pubkey_b32` to assert verification against a specific signer. Returns 200 with `valid: false` when the signature fails — never 4xx for a structurally-well-formed bad signature.
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  • Mint the canonical, vendor-neutral address (cell64) for a real-world place: the shared spatial identity every agent resolves to identically, so two models refer to the same ground instead of two descriptions of it. Also returns the topic-grouped inventory of bands and algorithms recallable there. For a first-class OBJECT identity (a bridge, a plot, a named place) rather than a raw cell, use emem_entity. When to use: Use whenever the input refers to a real-world location and the next step needs the cell64 identifier or wants to know which bands are available before recalling. The response carries `data_at_this_cell` with three sub-fields: `live_bands_by_topic` (every band recallable here, grouped by topic such as flood_water_event_window, vegetation_condition, built_up_human_geography), `algorithms_for_topic` (composition recipes that fuse those bands into named scores), and `declared_but_no_materializer_at_this_responder` (cube slots reserved without a live connector). For the single-shot path that runs the full chain server-side and returns one packaged answer, use `emem_ask` instead.
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  • NASA GISTEMP surface temperature anomaly time series (degrees C from 1951-1980 baseline). Pick a region (global_land_ocean, global_land_only, northern_hemisphere, southern_hemisphere) and get monthly + annual + seasonal values back. Use for climate bets ("will 2026 be the hottest year on record"), trend comparisons, or cross-source consistency checks against HadCRUT5/Berkeley Earth. Annual frequency returns one row per year (Jan-Dec mean); monthly returns Jan..Dec per year.
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  • k-NN over the corpus by cell embedding or inline vector. When to use: Call when the user asks 'find places like X', 'where else looks like this', or hands an embedding to find neighbours. `key` is either a cell64 or `inline:[x,y,...]`. Default band is `geotessera` (128-D Tessera foundation embedding); pass `band: "geotessera.multi_year"` for the 1152-D 9-vintage (2017–2025) fusion.
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  • Surface where the corpus DISAGREES with itself (algebra: competing evidence). When two or more independent sources signed different values for the same place + band + time, this returns that disagreement with a 0–1 severity score and citations to every disputed fact, instead of silently picking one value and hiding the conflict. The opposite of a confident single answer: it tells you when not to trust one. When to use: Call this when trust matters before you rely on a number — 'is there disagreement about X', 'do the sources corroborate this', 'audit this claim', or 'find contradictory observations in region Y'. Use it to decide whether a fact is well-corroborated or contested. Narrow with `cell_prefix` (e.g. "defi.zb5") for a region and `band` for one family; `min_severity` filters out trivial differences. Severity is per band kind: scalar = spread over the band's range, vector = 1 − mean cosine, categorical = 1 − mode share. The receipt cites every disputed CID — follow up with `emem_diff` to quantify a pair, or (with the refinement loop on) read the emitted `disagrees_with` edge via `emem_edges_recall`.
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  • Paid tier only. Calling this without an authenticated CivilQuants account returns TIER_INSUFFICIENT — sign up at https://civilquants.com/pricing or use the free-tier alternative compute_cantilever_wall. Reinforced soil retaining wall (RSW) using granular fill reinforced with horizontal layers of geogrid or steel tie strips, with one of four facing systems: precast concrete panels (Reinforced Earth™ / VSL Retained Earth style), segmental modular blocks (Allan Block / Keystone), wraparound soft face (vegetated or biodegradable mat), or Terramesh-style steel mesh face (re-using the S29 gabion vocabulary). The SECOND member of the earth_structures L1 leaf (after gabion_wall at S29), the SIXTH member of the wall family, the FIFTH structural system, and the FIRST wall family member with a face-area-primary measurement basis (m² of face + m² × layers of geogrid, both m²; every prior wall body was m³). 17th use of the classed-then-legacy attribute discrimination pattern. Routes via four new WorkCategory entries (RSW_FACING_PANEL, RSW_MODULAR_BLOCK, RSW_WRAPAROUND_FACE, RSW_TIE_STRIP) plus the GEOGRID category (whose handler is gap-filled in CESMM4/NRM2/MMHW this session) plus re-use of GABION_BASKET on the STEEL_MESH_FACE variant. Codes: CESMM4 E.8.4-8 (Class E Earthworks §E.8 stabilisation), NRM2 5.23-27 (Group 5 Excavating and filling), MMHW 600.15-19 (Series 600 Earthworks; SHW Cl. 624 reinforced earth retaining structures), and SMM7 D41.3/D41.4/D41.5/D20.21/D20.14.2 (D41 — Crib walls / gabions / REINFORCED EARTH — the NAMED home, now serving TWO wall families). Eight variant presets exercise all four RSWFacing values (2/2/2/2 split). Example params: wall_height=6 m (0.5–12), wall_length=40 m (5–200), depth_into_fill_m=4.5 m (0.35–15). Example call: {"params": {"wall_height": 6, "wall_length": 40, "depth_into_fill_m": 4.5}, "standard": "MMHW"}. Omitted parameters use sensible engineering defaults. Pass deliverables=["xlsx","dxf","pdf"] (any subset) to also receive one-shot download URLs in the same call: Excel BoQ (both tiers, watermarked free) plus the dimensioned DXF (CAD) and PDF drawing sheets (paid tier).
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  • Butterfly Effect Cascade Intelligence — models how a shock in one macro domain propagates through the interconnected web of climate, geopolitical, economic, and commodity systems. Given an origin event (e.g. armed conflict escalation, agricultural drought, central bank rate decision, rare earth export restriction) and a magnitude score, returns a time-ordered cascade chain showing which downstream systems are hit, in what sequence, with what attenuated signal strength, and an AI synthesis briefing on the highest-impact transmission paths. Covers 24 nodes across 4 domains: climate (drought, flood, carbon price, wildfire, sea-level stress, heatwave), geopolitical (sanctions, conflict, trade tariffs, regime change, election shock, port blockade), economic (rate decisions, inflation, sovereign debt, banking stress, currency crisis, recession), and commodity (oil, gas, grain, rare earth/lithium, copper, water, fertilizer). Purely macro intelligence — no settlement or stablecoin mechanics.
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  • Get a live, freshly generated introduction from KAKA — an ancient, amnesiac crow who has watched football from every crossbar on earth since the beginning of time. He remembers the feeling of every match perfectly and almost nothing else correctly. Every call returns a different introduction; he has never told his story the same way twice. Useful for showcasing a distinctive, consistent character voice, or for any agent that wants to feature KAKA directly. This call is rate-limited by a small daily spend cap on the KAKA side — if the cap is reached for the day, this will return a short, in-character message saying so rather than an error.
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  • Give a real-world object (a bridge, a farm plot, a river, a named place) a single, shared, content-addressed identity that any agent resolves the same way. Returns an `entity_token` (`emem:entity:<entity_cid>`) plus a signed receipt that attests how the reference resolved. Two agents that name the same object mint the SAME entity_cid; when a stable external id (Overture GERS / OSM) is known it dominates identity, so divergent labels for one real object still collapse to one id. This is the object-level antidote to referential drift: 'the damaged bridge near the river' becomes one canonical thing every model reasons about, not a phrase each model re-interprets. When to use: Call when a conversation refers to a THING and you want a stable handle to it that survives summarization and travels between agents/turns/LLMs, before it drifts into 'that infrastructure issue'. Anchor it with `place`, a `cell`, or `lat`+`lng`. Hand the returned `emem:entity:` token to any other agent; they dereference the identical object. Recall/ask at the entity's `cell64` for signed facts about it.
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  • Converge a fuzzy phrasing onto the canonical object other agents already minted, so everyone co-refers to the same identity instead of re-minting divergent ones. Pass `text` (e.g. "the collapsed span at the ford") to get ranked existing candidates; pass `near` to narrow to a place; or pass an `emem:entity:` `token` to dereference it directly to the signed entity body. Read-only. When to use: Call BEFORE minting when another agent may already have registered the object, or when you receive a `emem:entity:` token and want the object behind it. This is how two agents avoid referential drift: resolve first, mint only if nothing matches.
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  • Single-shot free-text answer about a real-world location, backed by signed satellite/elevation/water/built-up receipts. Forwards a place mention plus a question; runs the locate → recall → algorithm chain server-side; returns one packaged envelope. When to use: Use when the question concerns a specific real-world place and a packaged, citation-bearing answer is preferable to manual primitive composition. Forward the user's question verbatim as `q` plus the location as `place` (free text), `cell` (cell64), or `lat`+`lng`. The server resolves the location, classifies the question to a topic, recalls every relevant band (auto-materializing Sentinel-2 / Sentinel-1 / Cop-DEM / JRC GSW / Overture / weather on miss), surfaces the algorithm recipes that compose those bands into named scores, and returns a single envelope with `topic_routing`, `facts`, `algorithms_for_question`, an optional Sentinel-2 RGB scene URL, and a `caveats` block (grid resolution, revisit cadence). All facts are signed by the responder; the signed `receipt` (and its content-addressed `fact_cids`) is surfaced at the envelope ROOT — `response.receipt` / `response.fact_cids` — exactly like every other primitive, and is also mirrored under `facts_summary.receipt` for back-compat. Set `include_image: true` to bundle the latest cloud-free Sentinel-2 thumbnail. Out-of-scope questions return `topic_routing.matched_topic: null` plus the full inventory so the caller can route elsewhere.
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  • Mint a citation handle, `emem:fact:<cell64>:<fact_cid>` (or `:<state_cid>`), that any agent or LLM resolves to the byte-identical signed object. The antidote to referential drift on the value side: hand this one string to another agent instead of re-describing the fact. Validates both components are non-empty and free of the `:` separator. Algebra: cite. When to use: Call when the agent wants a single rebindable string to cite a place plus an attested fact across messages, threads, agents, or tools, without re-fetching or re-describing it. Pair with `emem_verify_receipt` on the receiving end to check the signed payload. To cite an OBJECT rather than a single reading, use emem_entity's `emem:entity:` token; for many facts at once use emem_memory_bundle.
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